Transparent layers such as polymers are complex and can contain defects which are not detectable with classical optical inspection techniques. With an interference microscope, tomographic analysis can be used to obtain initial structural information over the depth of the sample by scanning the fringes along the Z axis and performing appropriate signal processing to extract the fringe envelope. By observing the resulting XZ section, low contrast, sub-μm sized defects can be lost in the noise which is present in images acquired with a CCD camera. It is possible to reduce temporal and spatial noise from the camera by applying image processing methods such as image averaging, dark frame subtraction or flat field division. In this paper, we present some first results obtained by this means with a white light scanning interferometer on a Mylar polymer, used currently as an insulator in electronics and micro-electronics. We show that sub-μm sized structures contained in the layer, initially lost in noise and barely observable, can be detected by applying a combination of image processing methods to each of the scanned XY images along the Z-axis. In addition, errors from optical imperfections such as dust particles on the lenses or components of the system can be compensated for with this method. We thus demonstrate that XZ section images of a transparent sample can be denoised by improving each of the XY acquisition images. A quantitative study of the noise reduction is presented in order to validate the performance of this technique.